Integration of seismic data with downhole fluid analysis to predict the location of heavy hydrocarbon

ABSTRACT

Various implementations directed to the integration of seismic data with downhole fluid analysis to predict the location of heavy hydrocarbon are provided. In one implementation, a method may include receiving seismic data for a hydrocarbon reservoir of interest. The method may also include identifying geological features associated with a secondary gas charge from the seismic data. The method may further include determining the proximity of the geological features to the hydrocarbon reservoir of interest. The method may additionally include receiving preliminary downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest. The method may further include analyzing the preliminary DFA data to determine the equilibrium state of the hydrocarbon reservoir and to confirm the secondary gas charge in the hydrocarbon reservoir. The method may also include determining whether to perform one or more additional DFA&#39;s.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to U.S. Provisional Patent Application Ser. No. 61/947,258 filed on Mar. 3, 2014, which is incorporated by reference herein in its entirety.

BACKGROUND

One of the primary goals of an oil and gas operating company is to develop a reservoir asset in the most cost-efficient way. As such, it would be desirable for the operating company to identify and assess all the risks that may impair the drainage of this hydrocarbon accumulation before production starts and as field development progresses. For example, it would be desirable for the operating company to identify the level of spatial connectivity within reservoir units, i.e., to identify flow barriers caused either by the geological deposition of sediments, or by deposition of solid particles, heavy hydrocarbons, precipitated from reservoir fluids.

Before a drilling operation commences, a seismic survey may be performed whereby reflected seismology is used to explore, and thereby determine the properties of Earth's subsurface for the purpose of identifying features associated with hydrocarbon deposits. The seismic survey may be performed on land or water.

During or after a drilling operation, evaluations may be performed on the reservoir for various purposes, such as to manage the production of hydrocarbons from the reservoir. In one scenario, formation evaluation may involve drawing fluid from the reservoir into a downhole tool for testing or sampling. Various devices, such as probes or packers, may be extended from the downhole tool to isolate a region of the wellbore wall, and thereby establish fluid communication with the reservoir surrounding the wellbore. Fluid may then be drawn into the downhole tool using the probe or packer. Within the downhole tool, the fluid may be directed to one or more fluid analyzers and sensors that may detect properties of the fluid. The properties of the fluid may be used to determine reservoir architecture, connectivity, compositional gradients or the like.

SUMMARY

Various implementations directed to the integration of seismic data with downhole fluid analysis to predict the location of heavy hydrocarbon are provided. In one implementation, a method may include receiving seismic data for a hydrocarbon reservoir of interest. The method may also include identifying geological features associated with a secondary gas charge from the seismic data, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds. The method may further include determining the proximity of the geological features to the hydrocarbon reservoir of interest. The method may additionally include receiving preliminary downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest. The method may further include analyzing the preliminary DFA data to determine the equilibrium state of the hydrocarbon reservoir and to confirm the secondary gas charge in the hydrocarbon reservoir. The method may also include determining whether to perform one or more additional DFA's.

In another implementation, a method may include receiving seismic data for a hydrocarbon reservoir of interest. The method may also include identifying geological features associated with a secondary gas charge from the seismic data, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds. The method may further include receiving preliminary downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest. The method may additionally include analyzing the preliminary DFA data for fluid markers associated with the secondary gas charge in the hydrocarbon reservoir of interest. The method may further include determining whether secondary gas charge has occurred from the analysis of the preliminary DFA data. The method may also include predicting the presence of large disequilibrium gas-oil-ratio (GOR) gradients and saturation pressure gradients in the hydrocarbon reservoir based on the determination of the secondary gas charge.

Various implementations are also directed to a non-transitory computer readable medium having stored thereon a plurality of computer-executable instructions which, when executed by a computer, cause the computer to receive seismic data for a hydrocarbon reservoir of interest. The computer-executable instructions may also cause the computer to identify geological features in seismic data that are associated with a secondary gas charge, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds. The computer-executable instructions may further cause the computer to receive downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest. The computer-executable instructions may further cause the computer to analyze the DFA data to determine the equilibrium state of the hydrocarbon reservoir and to confirm the secondary gas charge in the hydrocarbon reservoir. The computer-executable instructions may further cause the computer to predict one or more locations of heavy hydrocarbon within the hydrocarbon reservoir of interest based on the identified geological features.

The above referenced summary section is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description section. The summary is not intended to be used to limit the scope of the claimed subject matter. Furthermore, the claimed subject matter is not limited to implementations that solve any disadvantages noted in any part of this disclosure. Indeed, the systems, methods, processing procedures, techniques, and workflows disclosed herein may complement or replace conventional methods for identifying, isolating, or processing various aspects of seismic signals or other data that is collected from a subsurface region or other multi-dimensional space, including time-lapse seismic data collected in a plurality of surveys.

BRIEF DESCRIPTION OF THE DRAWINGS

Implementations of various techniques will hereafter be described with reference to the accompanying drawings. However, it should be understood, that the accompanying drawings illustrate the various implementations described herein, and are not meant to limit the scope of various techniques described herein.

FIG. 1.1 illustrates a simplified diagrammatical view of a seismic survey operation being performed by a seismic truck to measure properties of the subterranean formation in connection with various implementations described herein.

FIG. 1.2 illustrates a simplified diagrammatical view of a drilling operation being performed by drilling tools suspended by a rig, and advanced into the subterranean formations to form a wellbore in connection with various implementations described herein.

FIG. 1.3 illustrates a simplified diagrammatical view of a wireline operation being performed by a wireline tool suspended by a rig, and lowered into the wellbore in connection with various implementations described herein.

FIG. 1.4 illustrates a simplified diagrammatical view of a production operation being performed by a production tool deployed from a production unit, or Christmas tree into the wellbore to draw fluid from the downhole reservoirs into surface facilities in connection with various implementations described herein.

FIG. 2 illustrates a flow diagram of a method for the integration of seismic data and downhole fluid analysis (DFA) to predict the location of heavy hydrocarbon in accordance with various implementations described herein.

FIG. 3 illustrates a diagrammatical view of a 2D seismic data plot in accordance with various implementations described herein.

FIG. 4 illustrates a rig with a downhole drilling tool in accordance with various implementations described herein.

FIG. 5 illustrates a downhole wireline tool in accordance with implementations of various technologies and techniques described herein.

FIG. 6 illustrates a computing system in which various implementations of various techniques described herein may be implemented.

DETAILED DESCRIPTION

The discussion below is directed to certain specific implementations. It is to be understood that the discussion below is for the purpose of enabling a person with ordinary skill in the art to make and use any subject matter defined now or later by the patent “claims” found in any issued patent herein.

It is specifically intended that the claims not be limited to the implementations and illustrations contained herein, but include modified forms of those implementations including portions of the implementations and combinations of elements of different implementations as come within the scope of the following claims.

Reference will now be made in detail to various implementations, examples of which are illustrated in the accompanying drawings and figures. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. However, it will be apparent to one of ordinary skill in the art that the present disclosure may be practiced without these specific details. In other instances, well-known methods, procedures, components, circuits and networks have not been described in detail so as not to obscure aspects of the embodiments.

It will also be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are used to distinguish one element from another. For example, a first object could be termed a second object, and, similarly, a second object could be termed a first object, without departing from the scope of the claims. The first object and the second object are both objects, respectively, but they are not to be considered the same object.

The terminology used in the description of the present disclosure herein is for the purpose of describing particular implementations and is not intended to be limiting of the present disclosure. As used in the description of the present disclosure and the appended claims, the singular forms “a,” “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will also be understood that the term “and/or” as used herein refers to and encompasses one or more possible combinations of one or more of the associated listed items. It will be further understood that the terms “includes” and/or “including,” when used in this specification, specify the presence of stated features, integers, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, operations, elements, components and/or groups thereof.

As used herein, the terms “up” and “down”; “upper” and “lower”; “upwardly” and downwardly”; “below” and “above”; and other similar terms indicating relative positions above or below a given point or element may be used in connection with some implementations of various technologies described herein. However, when applied to equipment and methods for use in wells that are deviated or horizontal, or when applied to equipment and methods that when arranged in a well are in a deviated or horizontal orientation, such terms may refer to a left to right, right to left, or other relationships as appropriate.

It should also be noted that in the development of any such actual implementation, numerous decisions specific to circumstance may be made to achieve the developer's specific goals, such as compliance with system-related and business-related constraints, which will vary from one implementation to another. Moreover, it will be appreciated that such a development effort might be complex and time-consuming but would nevertheless be a routine undertaking for those of ordinary skill in the art having the benefit of this disclosure.

The terminology and phraseology used herein is solely used for descriptive purposes and should not be construed as limiting in scope. Language such as “having,” “containing,” or “involving,” and variations thereof, is intended to be broad and encompass the subject matter listed thereafter, equivalents, and additional subject matter not recited.

Furthermore, the description and examples are presented solely for the purpose of illustrating the different embodiments, and should not be construed as a limitation to the scope and applicability. While any composition or structure may be described herein as having certain materials, it should be understood that the composition could optionally include two or more different materials. In addition, the composition or structure may also include some components other than the ones already cited. It should also be understood that throughout this specification, when a range is described as being useful, or suitable, or the like, it is intended that any value within the range, including the end points, is to be considered as having been stated. Furthermore, respective numerical values should be read once as modified by the term “about” (unless already expressly so modified) and then read again as not to be so modified unless otherwise stated in context. For example, “a range of from 1 to 10” is to be read as indicating a respective possible number along the continuum between about 1 and about 10. In other words, when a certain range is expressed, even if a few specific data points are explicitly identified or referred to within the range, or even when no data points are referred to within the range, it is to be understood that the inventors appreciate and understand that any data points within the range are to be considered to have been specified, and that the inventors have possession of the entire range and points within the range.

As used herein, the term “if” may be construed to mean “when” or “upon” or “in response to determining” or “in response to detecting,” depending on the context. Similarly, the phrase “if it is determined” or “if [a stated condition or event] is detected” may be construed to mean “upon determining” or “in response to determining” or “upon detecting [the stated condition or event]” or “in response to detecting [the stated condition or event],” depending on the context.

One or more implementations of various techniques for the integration of seismic data and downhole fluid analysis (DFA) to predict the location of heavy hydrocarbon will now be described in more detail with reference to FIGS. 1-6 in the following paragraphs.

Production Environment

FIGS. 1.1-1.4 illustrate simplified views of a production field 100 having a subterranean formation 102 containing reservoir 104 therein in connection with various implementations described herein. The production field 100 may be an oilfield, a gas field, or the like, and may be on land, water or sea.

FIG. 1.1 illustrates a diagrammatical view of a seismic survey operation being performed by a survey tool, such as a seismic truck 106.1, or marine seismic vessel (not shown), to measure properties of the subterranean formation 102 in connection with various implementations described herein.

The survey operation may be a seismic survey operation for producing sound vibrations or acoustic signals. In FIG. 1.1, one such sound vibration, e.g., sound vibration 112 generated by source 110, may reflect off horizons 114 in earth formation 116. A set of sound vibrations may be received by sensors, such as geophone-receivers 118, situated on the earth's surface, or hydrophones (not shown) deployed beneath the surface of the water as part of a streamer array. The data received 120 may be digitized, and provided as input data to a computer 122.1 of a seismic truck 106.1, or marine vessel (not shown), and responsive to the input data, computer 122.1 generates seismic data output 124. This seismic data output 124 may be stored, transmitted, or further processed as desired, for example, by data reduction.

FIG. 1.2 illustrates a diagrammatical view of a drilling operation being performed by drilling tools 106.2 suspended by a rig 128, and advanced into the subterranean formations 102 to form a wellbore 136 in connection with various implementations described herein. Mud pit 130 may be used to draw drilling mud into the drilling tools via flow line 132 for circulating drilling mud down through the drilling tools, then up wellbore annulus 136 and back to the surface. The drilling mud may be filtered and returned to the mud pit. A circulating system may be used for storing, controlling, or filtering the flowing drilling mud. The drilling tools may be advanced into subterranean formations 102 to reach reservoir 104. Each well may target one or more reservoirs. The drilling tools may be adapted for measuring downhole properties using logging while drilling (LWD) tools. The LWD tools may also be adapted for taking core sample 133 as shown.

Computer facilities may be positioned at various locations about the production field 100 (e.g., the surface unit 134), or at remote locations. Surface unit 134 may be used to communicate with the LWD tools, or offsite operations, as well as with other surface or downhole sensors. Surface unit 134 may be capable of communicating with the LWD tools to send commands to the LWD tools, and to receive data therefrom. Surface unit 134 may also collect data generated during the drilling operation and produce data output 135, which may then be stored or transmitted.

Sensors (S), such as gauges, may be positioned about production field 100 to collect data relating to various production field operations as described previously. As shown, sensor (S) may be positioned in one or more locations in the drilling tools, and/or at rig 128 to measure drilling parameters, such as weight on bit, torque on bit, pressures, temperatures, flow rates, compositions, rotary speed, or other parameters of the field operation. Sensors (S) may also be positioned in one or more locations in the circulating system.

Drilling tools 106.2 may include a bottom hole assembly (BHA) (not shown), generally referenced, near the drill bit (e.g., within several drill collar lengths from the drill bit). The BHA may include capabilities for measuring, processing, and storing information, as well as communicating with surface unit 134. The BHA may further include drill collars for performing various other measurement functions.

The BHA may include a communication subassembly that communicates with surface unit 134. The communication subassembly may be adapted to send signals to, and receive signals from the surface using a communications channel, such as mud pulse telemetry, electro-magnetic telemetry, or wired drill pipe communications. The communication subassembly may include, for example, a transmitter that generates a signal, such as an acoustic or electromagnetic signal, which is representative of the measured drilling parameters. It may be appreciated by one of skill in the art that a variety of telemetry systems may be employed, such as wired drill pipe, electromagnetic or other known telemetry systems.

The wellbore may be drilled according to a drilling plan that is established prior to drilling. The drilling plan may set forth equipment, pressures, trajectories and/or other parameters that define the drilling process for the well site. The drilling operation may then be performed according to the drilling plan. However, as information is gathered, the drilling operation may need to deviate from the drilling plan. Additionally, as drilling or other operations are performed, the subsurface conditions may change. The earth model may also need adjustment as new information is collected.

The data gathered by sensors (S) may be collected by surface unit 134 and/or other data collection sources for analysis or other processing. The data collected by sensors (S) may be used alone or in combination with other data. The data may be collected in one or more databases, or transmitted on or offsite. The data may be historical data, real time data, or combinations thereof. The real time data may be used in real time, or stored for later use. The data may also be combined with historical data or other inputs for further analysis. The data may be stored in separate databases, or combined into a single database.

Surface unit 134 may include transceiver 137 to allow communications between surface unit 134, and various portions of the production field 100 or other locations. Surface unit 134 may also be provided with or functionally connected to one or more controllers (not shown) for actuating mechanisms at production field 100. Surface unit 134 may then send command signals to production field 100 in response to data received. Surface unit 134 may receive commands via transceiver 137, or may itself execute commands to the controller. A processor may be provided to analyze the data (locally or remotely), make decisions, or actuate the controller. In this manner, production field 100 may be selectively adjusted based on the data collected. This technique may be used to optimize portions of the field operation, such as controlling drilling, weight on bit, pump rates, or other parameters. These adjustments may be made automatically based on computer protocol, or manually by an operator. In some cases, well plans may be adjusted to select optimum operating conditions, or to avoid problems.

FIG. 1.3 illustrates a diagrammatical view of a wireline operation being performed by a wireline tool 106.3, suspended by a rig 128, and lowered into the wellbore 136 in connection with various implementations described herein. Wireline tool 106.3 may be adapted for deployment into wellbore 136 for generating well logs, performing downhole tests or collecting samples. Wireline tool 106.3 may be used to provide another method and apparatus for performing a seismic survey operation. Wireline tool 106.3 may, for example, have an explosive, radioactive, electrical, or acoustic energy source 144 that sends and/or receives electrical signals to surrounding subterranean formations 102 and fluids therein.

Wireline tool 106.3 may be operatively connected to, for example, geophones 118 and a computer 122.1 of a seismic truck 106.1 of FIG. 1.1. Wireline tool 106.3 may also provide data to surface unit 134. Surface unit 134 may collect data generated during the wireline operation, and may produce data output 135, which may be stored or transmitted. Wireline tool 106.3 may be positioned at various depths in the wellbore 136 to provide a survey, or other information relating to the subterranean formation 102.

Sensors, such as gauges, may be positioned about production field 100 to collect data relating to various field operations as described previously. Sensors may be positioned in wireline tool 106.3 to measure downhole parameters which relate to, for example porosity, permeability, fluid composition, and other parameters of the field operation.

FIG. 1.4 illustrates a simplified diagrammatical view of a production operation being performed by a production tool 106.4, deployed from a production unit, or Christmas tree 129, into the completed wellbore 136 to draw fluid from the downhole reservoirs into surface facilities 142 in connection with various implementations described herein. The fluid flows from reservoir 104 through perforations in the casing (not shown), and into production tool 106.4 in wellbore 136, and to surface facilities 142, via gathering network 146.

Sensors, such as gauges, may be positioned about production field 100 to collect data relating to various field operations as described previously. Sensors may be positioned in production tool 106.4, or associated equipment, such as Christmas tree 129, gathering network 146, surface facility 142, or the production facility, to measure fluid parameters, such as fluid composition, flow rates, pressures, temperatures, and other downhole parameters of the production operation.

Production may also include injection wells for added recovery. One or more gathering facilities may be operatively connected to one or more of the well sites for selectively collecting downhole fluids from the well site(s).

While FIGS. 1.2-1.4 illustrate tools used to measure properties of a production field, such as an oilfield or gas field, it may be appreciated that the tools may be used in connection with other operations, such as mines, aquifers, storage, or other subterranean facilities. Also, while certain data acquisition tools are depicted, it may be appreciated that various measurement tools capable of sensing parameters, such as seismic two-way travel time, density, resistivity, production rate, etc., of the subterranean formation and/or its geological formations may be used. Various sensors may be located at various positions along the wellbore, and/or the monitoring tools to collect, and/or monitor the desired data. Other sources of data may also be provided from offsite locations.

The field configurations of FIGS. 1.1-1.4 may be an example of a field usable with oilfield or gas field application frameworks. At least part of the production field 100 may be on land, water or sea. Also, while a single field measured at a single location may be depicted, oilfield or gas field applications may be utilized with any combination of one or more oilfields, and/or gas fields, one or more processing facilities, and one or more well sites.

The data collected from various sources, such as the data acquisition tools of FIGS. 1.1-1.4, respectively, or others not depicted, may then be processed and/or evaluated. The seismic data from the data acquisition tool 106.1 of FIG. 1.1 may be used by a geophysicist to determine characteristics of the subterranean formations, and identify features associated with oil and/or gas deposits. The core and/or log data from data acquisition tool 106.2 of FIG. 1.2, and/or data acquisition tool 106.3 of FIG. 1.3, may be used by a geologist to determine various characteristics of the subterranean formation. The production data from data acquisition tool 106.4 of FIG. 1.4 may be used by the reservoir engineer to determine fluid flow reservoir characteristics. The data analyzed by the geologist, geophysicist and the reservoir engineer may be analyzed to determine reservoir fluid geodynamics (RFG) for the purpose of flow assurance. The data analyzed by the geologist, geophysicist, and the reservoir engineer may be analyzed using modeling techniques.

Attention is now directed to methods, techniques, and workflows for processing, and/or transforming collected data that are in accordance with some implementations. Some operations in the processing procedures, methods, techniques, and workflows disclosed herein may be combined, and/or the order of some operations may be changed. In the geosciences and other multi-dimensional data processing disciplines, various interpretations, sets of assumptions, or domain models such as velocity models, may be refined in an iterative fashion. This iterative refinement can include use of feedback loops executed on an algorithmic basis, such as via a computing system, as discussed later, and/or through manual control by a user who may make determinations regarding whether a given action, template, or model has become accurate.

Analyzing a Reservoir

As mentioned above, a reservoir disposed in a subterranean formation may contain hydrocarbons. In particular, the hydrocarbons may develop from the thermal cracking of organic matter deposited in source rocks as they are buried deeper in the earth's crust by the deposition of newer sediments. Fluids containing these hydrocarbons may eventually be expelled from the source rock and migrate, such as through faults and fractures, until they are trapped in a reservoir rock. Such migration of hydrocarbons may be referred to as a primary charge. In particular, reservoir fluids disposed in these reservoirs may contain the hydrocarbons, where the hydrocarbons may take the form of oil, gas condensate, and/or the like.

In one scenario, if the migration of fluids ceases and the reservoirs behave as a closed system, then the reservoir fluids may eventually reach a state of chemical and thermodynamic equilibrium. Gravity may act as a force on the reservoir. In addition, depending on the length of the hydrocarbon column and the hydrocarbon composition, there may be composition gradients within the reservoir. However, some reservoirs may not behave as an ideal closed system as described above. Instead, one or a combination of the following situations may occur: geologic events may alter the reservoir structure after the primary charge, more thermally mature fluids, such as gas, may arrive to the reservoir, this may be referred to as a secondary or late charge, hydrocarbons may escape via flow channels or a compromised cap seal, biodegradation at sufficiently low temperature and mixing with biogenic methane, biogenic methane arriving at the reservoir, water washing or the like. Such reservoirs may have reservoir fluids which exist in a state of non-equilibrium, and the fluid composition may not be homogeneous.

In another scenario, the primary and secondary charge may result in a mixing of the reservoir fluids, and the nature of the mixing may be such that instability, and precipitation and/or concentration of the solid hydrocarbon fraction, or asphaltene may occur. Asphaltenes are solids that precipitate when an excess of n-heptane or pentane is added to crude oil. Precipitation may also occur during oil production, as a result of destabilization, which may be the result of changes in temperature, pressure and/or the chemical composition of the crude. Such precipitation may result in the creation of heavy hydrocarbon. For example, an asphaltene layer may be deposited up-structure where it coats grain surfaces forming bitumen, which may not preclude permeability and the flow of hydrocarbons. Alternatively, the asphaltene may be deposited up-structure as a layer of solid hydrocarbon, which may preclude permeability and therefore the flow of hydrocarbons. Further, the precipitation may be deposited near the base of the reservoir as a tar mat and/or heavy and viscous oil, which may form a thick impermeable layer of asphaltene material.

The presence of heavy hydrocarbons may diminish fluid mobility within a reservoir. For example, heavy hydrocarbons may seal the reservoir from adjacent aquifers, thereby reducing aquifer support. Heavy hydrocarbons may also reduce the production index by flowing simultaneously with light hydrocarbons contained in the reservoir formations. In addition, mobile heavy hydrocarbon may further reduce the production index by depositing a coating of thick tar on production tubular. However, distinguishing heavy hydrocarbon from light hydrocarbon using data obtained from seismic surveys, and/or downhole tool logs by traditional methods may be difficult due to their low seismic velocity contrast and small relatively size.

In yet another scenario, the reservoir may be compartmentalized such that it lacks a level of spatial connectivity within reservoir units (i.e., parts of the reservoir). A compartmentalized reservoir may consist of two or more compartments that effectively are not in hydraulic communication. Two types of reservoir compartmentalization may include vertical and lateral compartmentalization. Lateral compartmentalization may occur as a result of faulting or stratigraphic changes in the reservoir, while vertical compartmentalization may occur from sealing barriers such as shale.

The presence of heavy hydrocarbons, reservoir compartmentalization and non-equilibrium hydrocarbon distribution can significantly hinder production, and may make a difference between an economically-viable field and an economically-nonviable field. Techniques aimed at understanding reservoir fluid geodynamics for the purpose of flow assurance may allow an operator to factor into a well development program the economic risks associated with the presence of these features, and may ultimately raise production.

Integration of Seismic Data and Downhole Fluid Analysis (DFA)

In one implementation, and as further described below, an integration of seismic analysis and DFA may be used to provide information that may be used to accurately identify heavy hydrocarbons and their distribution in the reservoir of interest. In particular, seismic analysis and downhole fluid analysis may be used to identify subsurface features and fluid markers that may be associated with secondary (or late) gas charging in the reservoir.

FIG. 2 illustrates a flow diagram of a method 200 for the integration of seismic data with DFA to predict the location of heavy hydrocarbon in accordance with various implementations described herein. In one scenario, method 200 uses seismic data in combination with DFA to understand reservoir fluid geodynamics (RFG). Understanding of RFG may help predict the presence of heavy hydrocarbon layers, and their location within the reservoir. An operator of reservoir may wish to obtain this information for many reasons, for example to take into account the economic risk associated with the presence of these heavy hydrocarbons in a well development program, or for flow assurance purposes.

In one implementation, method 200 may be performed by one or more computer applications, where the computer applications may implement one or more of the electronics and processing system, controller of the fluid analysis module, and/or the computer system described below. It should be understood that while method 200 indicates a particular order of execution of operations, in some implementations, certain portions of the operations might be executed in a different order. Further, in some implementations, additional operations or blocks may be added to the method. Likewise, some operations or blocks may be omitted.

At block 210, seismic data may be received from one or more seismic survey operations performed by a survey tool, such as the seismic truck 106.1 of FIG. 1.1, or marine seismic vessel. In one implementation, the land and/or marine seismic data may have been acquired as part of a 2D or 3D survey exploration process to identify subterranean geological formations associated with hydrocarbon deposits in connection with various implementations described herein. In a further implementation, the seismic data may be time-lapse, or 4D seismic data obtained from repeated seismic production surveys over a producing hydrocarbon reservoir, which may be used to determine changes within the reservoir that may be the result of hydrocarbon production, or injection of water, and/or gas into reservoir as part of a well development program. In yet another implementation, seismic data may have been acquired as part of method 200. An example of a simplified diagrammatical view of a 2D seismic data plot in accordance with various implementation described herein is depicted in FIG. 3.

At block 220, the seismic data may be processed to identify subterranean geological features associated with secondary gas charging into the hydrocarbon filled reservoir. In one scenario, these subterranean geological features may include gas pockets, gas chimneys or salt deposits. Referring to the 2D seismic data plot of FIG. 3, bright spots in the seismic data may indicate the presence of gas pockets. A gas chimney may be associated with a subsurface leakage of gas from a poorly sealed hydrocarbon accumulation, and may result in secondary gas charging of a hydrocarbon reservoir as described herein. Referring to FIG. 3, gas chimneys may be visible in the seismic data as areas of poor data quality, or push-downs. In one implementation, the seismic data may be processed to enhance the identification of gas chimneys.

Seismic data may also indicate the presence of salt formations in communication with the reservoir. Associated with these salt formations may be salt welds, the boundary between the salt formation and reservoir formation, which may act as conduits for secondary gas charging. The resolution, or bucket (bin) size of the seismic survey may be insufficient to identify the presence of a salt weld directly, and gas (bright spots) within it, unless the salt weld is sizeable. However, the presence of the salt weld and secondary gas charging may be inferred if there are bright spots in the seismic data proximate to the salt reservoir boundary.

At block 230, the seismic data may be analyzed to determine if the proximity of the identified subterranean geological feature to the hydrocarbon reservoir indicates that it may be in gas communication (or in connectivity) with the hydrocarbon reservoir. In some implementations, the analysis at block 230 may be applicable to a wellbore or a subterranean associated with a hydrocarbon reservoir. In another implementation, since salt deposits are frequently associated with, and in close proximity to hydrocarbon reservoirs, the determining factor may be the analysis at block 220, i.e., whether the salt weld has bright spots associated with it. In yet another implementation, whether gas chimneys are in communication with a hydrocarbon reservoir may be determined by a predetermined threshold spatial distance. The predetermined threshold spatial distance may depend on the size of the gas chimney, and/or hydrocarbon reservoir. In yet another implementation, geological proximity may be inferred by the presence of permeable sedimentary formations, which may act as a conduit. It should be understood that other techniques known to a person of ordinary skill in the art for determining the proximity may be used herein.

At block 240, preliminary DFA data may be received from one or more DFA measurement stations of a wellbore, at different locations within the reservoir. The preliminary DFA data may be determined during drilling or thereafter. In one implementation, the preliminary sample may be obtained using a downhole tool, such as those described below with respect to FIGS. 4 and 5. Further, as described below with respect to FIGS. 4 and 5, a computing application associated with a fluid communication module, and/or fluid analysis module may be used to determine the preliminary DFA data in substantially real time. In a further implementation, the computing application associated with the fluid communication module and/or fluid analysis module may operate in conjunction with a surface computing application, such as the electronics and processing system 506, to determine the first DFA data. The details of DFA are provided below in a section labeled Downhole Fluid Analysis.

The preliminary first DFA data may include one or more measurements of optical density, fluid fluorescence, fluid composition, fluid color, the gas-oil ratio (GOR), temperature, pressure, viscosity, density, resistivity, pH or H₂S levels, concentrations of several alkane components and groups in the first fluid sample (e.g., fractional amounts of C₁, C₂, C₃-C₅, C₆₊, CO₂, H₂O, and the like), and/or the like.

At block 250, the preliminary DFA data may be analyzed to determine whether a reservoir may be in disequilibrium. In one implementation, the preliminary DFA data may be analyzed to determine whether the GORs can be matched to cubic equations of state (EOS), and thereby determine whether any secondary gas charge has had time to equilibrate. In one scenario, the amount of available preliminary DFA data may only allow an inference that the reservoir is in disequilibrium.

Further, the preliminary DFA data may be analyzed for fluid markers that may be associated with secondary gas charging. These fluid markers may include the asphaltene content of the hydrocarbon reservoir and GOR. Secondary gas charging may be inferred from the organic solid deposition, asphaltene content, and the presence of solution gas. For example, a high asphaltene level at the bottom of the reservoir or high GOR at the top of the reservoir may be associated with secondary gas charging. The DFA data may be analyzed by optical, photoacoustic, or other techniques known to a person of ordinary skill in the art.

In particular, one or more EOS models of the thermodynamic behavior of the reservoir fluid may be used to predict the reservoir DFA data at different locations within the reservoir. Although various techniques described herein are with reference to a reservoir, it should be understood that in some implementations the techniques may be applied to a wellbore. In comparing the preliminary DFA data to the predicted DFA data, it may be assumed that there is connectivity between the spatial locations within the reservoir and thermodynamic equilibrium. Thus, the predicted DFA data may be used to confirm that they correspond to the expected reservoir architecture. In particular, connectivity (i.e., non-compartmentalization) and equilibration of the reservoir can be indicated by a moderate decrease of GOR values with increasing depth, a continuous increase of asphaltene content as a function of depth, a continuous increase of fluid density and/or fluid viscosity as a function of depth, and/or the like. Accordingly, the use of the EOS models to determine predicted DFA data may offer a baseline for the reservoir against which the preliminary DFA data can be compared, and thereby verification of whether the reservoir is in equilibrium. Agreement between the preliminary DFA data and the predicted DFA data may imply connectivity between the spatial locations. On the other hand, disagreement between the preliminary DFA data and the predicted DFA may be the result of geologic events that may alter the reservoir structure after the primary charge, such as thermally mature fluids from secondary gas charging migrating into the reservior and/or geolgical events that may have caused compartmentalization.

If the preliminary DFA data differs from the predicted DFA data by a threshold amount, it may then be determined that the reservoir is in a non-equilibrium state and/or compartmentalized. For example, non-equilibrium and/or compartmentalization can be indicated by a reversing trend in GOR (such as if lower GOR is found higher in the column), discontinuous asphaltene content (or if higher asphaltene content is found higher in the column), discontinuous fluid density and/or fluid viscosity (or if higher fluid density and/or fluid viscosity is found higher in the column), variations in fluid composition, fluid properties indicated by the preliminary DFA data that are larger than those of the predicted DFA data, and/or the like. In one implementation, the threshold amount may be equal to an amount greater than or equal to a monotonic variation between the preliminary DFA data and the predicted DFA data.

In one implementation, a surface computing system, such as the electronics and processing system, may estimate the fluid properties and/or fluid behavior using the EOS models. The estimated fluid properties of the wellbore may include: GOR, condensate-gas ratio (CGR), fluid color, density of each phase, volumetric factors and compressibility, heat capacity, saturation pressure (i.e., bubble or dew point), optical density, the distribution of a solid fraction of the reservoir fluid (e.g., asphaltenes, resins, and/or the like), viscosity, and/or the like. In one implementation, the EOS models may estimate the fluid properties and/or fluid behavior as a function of depth, such that the fluid properties and/or fluid behavior are predicted for one or more additional measurement stations in the wellbore.

In such an implementation, the surface computing system may perform the estimations based on the preliminary DFA data. The surface computing system may perform the estimations based on DFA data from multiple measurement stations.

In another implementation, the equilibrate analysis may be used to infer the geological age of the hydrocarbon reservoir, and thereby obtain a better understanding the reservoir fluid geodynamics. For example, the analysis may be used to determine whether the geological age of the hydrocarbon reservoir is young, 1-3 million years, or old, 100 million years. At block 260, a risk assessment may be performed to determine whether heavy hydrocarbon may be present within the hydrocarbon reservoir, which is the result of secondary gas charging, and whether there is disequilibrium. The risk assessment may be for flow assurance purposes, and/or to determine whether additional DFA measurement stations are needed to locate, test and monitor heavy hydrocarbon and/or further support a determination of whether the wellbore, reservoir is equilibrated.

In one implementation, the risk assessment may be determined by any indication of secondary gas charging, such as the proximity of subterranean geological features associated with gas charging, as determined by seismic analysis at block 230, and fluid markers obtained from preliminary DFA data, which may infer gas charging and/or wellbore and/or reservoir disequilibrium as determine at block 250.

If the analysis at block 260 determines that additional DFA data is needed from additional downhole fluid samples then additional fluid samples may be obtained in a similar manner as the preliminary fluid samples, and the additional DFA data may be determined in a similar manner as the preliminary DFA data described herein. Further, in the case of the identified geological feature being a gas chimney, it may be possible to infer the location of the additional DFA measurement stations based on the size of the gas chimney.

At block 270, the size of a gas chimney identified at block 220 is determined. In one implementation, a gas chimney may be classified as large if its physical size is determined to be greater than one kilometer (1 km). A gas chimney may also be classified as large if its size is comparable to, or greater than that of the hydrocarbon reservoir. A gas chimney may be classified as small if its physical size is about four to five hundred meters (4-500 m), or if its size is about one third (⅓) or less of the hydrocarbon reservoir, with the relative size with respect to the hydrocarbon reservoir being the determining factor.

If the analysis at block 270 classifies the gas chimney as large, then at block 280 the additional DFA measurement stations, from which additional DFA fluid samples and data may be obtained, may be located at the top of the wellbore and/or reservoir. In one scenario, a large gas chimney may be associated with a high rate of gas charging into the reservoir. The high rate of gas charging may result in a GOR that rapidly increases. The rapidly increasing GOR may cause asphaltenes to destabilize before they can migrate away. The high rate of gas charging, which may be associated with a large gas chimney, may therefore result in a phase-separated bitumen layer up-structure, or substantially near the top of the wellbore and/or reservoir as described herein.

The presence of a bitumen zone may be determined by analysis of fluid formation samples obtained from coring, sidewall coring and whole core. Further, the bitumen zone may be inferred if the DFA data identifies low asphaltene content mobile oil, whose asphaltene onset pressure, as measured by a pressure volume temperature (PVT) laboratory, is substantially the same, as the reservoir pressure, as measured by a modular formation dynamics tester (MDT).

If the analysis at block 270 classifies the gas chimney as small, then at block 290, the additional DFA measurement stations may be located at the base of the wellbore and/or reservoir. In one scenario, a small gas chimney may be associated with a low rate of gas charging into the reservoir. This process may cause asphaltenes to aggregate. Further, the aggregated asphaltenes may form clusters, which may be described by a model, such as the Yen-Mullins model.

In one scenario, gravity may act upon the relatively large and dense asphaltene clusters causing them to migrate predominantly towards the base of the reservoir. In another, the migration towards the base of the reservoir may be due the effect of solubility, whereby the secondary gas charge may result in high (GOR) gas content oils. The energy cost associated with these high gas content oils mixing with the asphaltenes may cause phase separation of the gas and asphaltenes. As more gas enters the top of the reservoir, a descending gas-rich front may be created. This descending gas-rich front may push the asphaltenes substantially towards the base of the reservoir. Therefore, a tar mat may form at the base of the reservoir as a result of a low rate gas charge associated with a small gas chimney. In yet another scenario, an insufficient amount of gas may entered the reservoir to form a tar mat, however sufficient asphaltenes may still be concentrated at the base of the reservoir to form a layer of heavy hydrocarbon oil.

A tar mat may be too heavy to be sampled by a modular formation dynamics tester (MFT); therefore its presence may have to be determined by Ultraviolet (UV) illumination of fluid formation samples obtained from coring, sidewall coring and whole core. Under UV illumination the tar may appear dark, and below light oil, which may appear bright under UV illumination.

The presence of heavy oil may be determined by the high asphaltene content of fluid formation samples, which may be obtained by a MFT and/or coring, sidewall coring and whole core. Further, the presence of heavy oil may be determined by optical density or photoacoustic analysis or other DFA techniques known to a person of ordinary skill in the art.

If the analysis at block 270 is unable to classify the gas chimney as either large or small, or the subterranean geological feature is determined to be a salt welt at block 220, then additional DFA measurement stations may be located, and additional DFA fluid samples and data, may have to be obtained substantially throughout the reservoir.

In one scenario, the additional DFA data may also include one or more measurements of optical density, fluid color, fluid fluorescence, fluid composition, GOR, temperature, pressure, viscosity, fluid density, resistivity, pH or H₂S levels, concentrations of several alkane components and fractional amounts of C₁, C₂, C₃-C₅, C₆₊, CO₂, H₂O, and/or the like.

In one implementation, DFA may be further combined with core analyses, mud logging analyses of drilled rock cuttings, basic petrophysical logs (gamma-ray, resistivity, and neutron-density), advanced petrophysical logs (elemental analysis logs, magnetic resonance logs, and porosity logs), and mobility measurements from a formation tester to further identify heavy hydroncarbons.

In one example, DFA data may be integrated with such analysis to provide information of field-wide or localized fluid instabilities, which may give rise to departures from the baseline thermodynamic equilibrium state and may provide information for field development planning. In another example, this may provided information for developing a fluid model of the hydrocarbon reservoir in real time. The fluid model may be used to understand the properties and distribution of hydrocarbon fluids in a reservoir formation.

In one implementation, the additional DFA fluid samples may be in the same wellbore as the preliminary DFA fluid samples, such that the additional DFA samples are at a different depth than the preliminary DFA fluid samples. Thus, the additional DFA data may correspond to the same wellbore as the preliminary DFA data. In another implementation, the additional DFA fluid samples may be in a different wellbore than the preliminary DFA fluid samples. Thus, the additional DFA data may correspond to a different wellbore than the preliminary DFA data in what is presumed to be the same reservoir unit.

In sum, analyzing a reservoir using seismic data and DFA, as described above, may provide information that can be used to determine reservoir fluid geodynamics for a reservoir of interest. For example, reservoir fluid geodynamics may be used to determine whether there has been a geological occurrence associated with the formation of heavy hydrocarbon, such as secondary gas charging, and whether the reservoir has had time to equilibrate. In particular, the integration of seismic data and DFA may be used to identify the presence and location of heavy hydrocarbons.

As will be understood by a person of ordinary skill in the art, combing the analysis of seismic data with DFA to identify gas charging has many applications. For example, gas charging may be associated with significant GOR gradients. Accordingly, this method may be used to assess when large disequilibrium GOR gradients and saturation pressure gradients may be present within the reservoir and/or wellbore.

FIG. 3 illustrates a diagrammatical view of a 2D seismic data plot in accordance with various implementations described herein. The 2D seismic data may have been acquired before drilling operations commenced as part of a 2D survey exploration process to identify subterranean geological formations associated with hydrocarbon deposits. Alternatively, the seismic data may have been acquired as time-lapse seismic data. This time lapsed seismic data may have been obtained from repeated seismic production surveys over a producing hydrocarbon reservoir, and may be used to determine changes within the reservoir. These changes may be the result of hydrocarbon production, or injection of water and/or gas into reservoir as part of a well development program. In one implementation, the 2D seismic data may have been acquired as part of the method 300 described herein.

The horizontal axis of the 2D seismic data plot represents distance. The horizontal axis is further subdivided into increments. The increments may make it easier for a user to visualize the size of geological features depicted in the seismic data, and/or may be representative of the seismic survey bucket or bin size. The vertical axis represents the time it takes for the reflections from a controlled energy source to reach a plurality of receivers, from which it may be possible to estimate the depth of the geological feature causing the reflections. The vertical axis is also subdivided into increments, which may make it easier for a user to visualize the depth of geological features depicted in the seismic data.

As shown in FIG. 3, the seismic data plot may indicate the presence of geological features associated with hydrocarbon deposits. For example, the seismic data may contain bright spots, which may indicate deposits of hydrocarbons or the presence of gas. The bright spots may be the result of gas collecting in porous rock formations, which may result in stronger seismic reflections (contrast), than porous rock filled with a fluid such as water and/or the adjacent rock formations. The acoustic contrast may be the result of the reduced velocity of sound passing through porous rock formations containing gas.

FIG. 3 further illustrates a gas chimney, the mixing of gas with sedimentary layers and gas migration. The gas may migrate into a reservoir already filled with black oil, which may have been generated earlier as a result of a primary charge. As disclosed herein, this may be referred to as secondary gas charging, and may impact the distribution of asphaltenes within the reservoir resulting in the formation of a bitumen zone, or a tar mat and/or heavy oil. A gas chimney may be associated with a subsurface migration (leakage) of gas from a poorly sealed hydrocarbon accumulation. A gas chimney may be visible in seismic data as an area of poor data quality, or may be visible as a push-down. A push-down may be visible in the seismic data result due to the rock-formations beneath the gas-bearing rock appearing deeper than they are due to relatively low velocity of sound through these gas-bearing rock formations above them.

Downhole Fluid Analysis

As mentioned above, DFA may be used in conjunction with seismic analysis to identify variations in fluid properties of the reservoir, which may in turn be used to detect heavy hydrocarbons, compartmentalization and/or non-equilibrium hydrocarbon distribution in the reservoir. In particular and as further described below, DFA may provide, in real time or substantially real time, geochemical information used to identify fluid generation pathways, biodegradation, reservoir tops, fault, and cap rock sealing properties, reservoir compartmentalization, fluid associations, and/or the like for the reservoir of interest. In such an implementation, DFA may be used to identify whether the reservoir contains considered biogenic or thermogenic material.

As will be described with respect to FIGS. 5-6, DFA and may provide hydrocarbon and non-hydrocarbon (CO₂) composition information to generate one or more models of reservoir fluid in the reservoir of interest.

For example, measurements obtained using DFA at different spatial locations in the reservoir may be contrasted with a prediction model derived from these measurements. In one implementation, agreement between the measurements and the model may imply connectivity between the spatial locations, provided that the fluid samples obtained from the spatial locations are in thermodynamic equilibrium.

On the other hand, disagreement between the measurements and the model may be further investigated to identify possible causes of instability that preclude thermodynamic equilibrium. As noted above, such causes may include geologic events that may alter the reservoir structure after the primary charge, thermally mature fluids that may arrive to the reservoir (secondary gas charging), hydrocarbons that may escape via flow channels or a compromised cap seal, ongoing and/or prior biodegradation at sufficiently low temperature and mixing with biogenic methane, biogenic methane arriving at the reservoir, water washing, and/or the like. In addition, analyzed data from the DFA, and seismic surveys could be used better understand RFG, and thereby to ascertain information relating to migration of the reservoir fluids, origin of the fluids, composition of the fluids, and/or the like.

Various implementations of well site systems described herein may be used to employ an integration of DFA and Seismic survey data, including a well site system that combines one or more implementations discussed below with respect to FIGS. 5 and 6 beneath.

After conducting the DFA of one or more reservoir fluid samples, the results of the DFA may be related to one or more equation of state (EOS) models of the thermodynamic behavior of the reservoir fluid in order to characterize the reservoir fluid at different locations within the reservoir. In particular, computer-based modeling and simulation techniques may use the EOS models to estimate the fluid properties and/or behavior of reservoir fluid within the reservoir. In one implementation, a surface computing system, such as the electronics and processing system 506 described below, may estimate the fluid properties and/or fluid behavior using the EOS models. In such an implementation, the surface computing system may perform the estimations based on received DFA data. The received DFA data may include measurements and/or calculations for optical density, fluid fluorescence, fluid composition, the GOR, pressure, volume, temperature, fluid density, fluid viscosity, and/or the like.

The EOS models may represent the phase behavior of the reservoir fluid, and can be used to compute fluid properties, such as: GOR, condensate-gas ratio (CGR), density of each phase, volumetric factors and compressibility, heat capacity and saturation pressure (bubble or dew point). Thus, the EOS models can be solved to obtain saturation pressure at a given temperature. Moreover, GOR, CGR, phase densities, and volumetric factors may be byproducts of the EOS models. Transport properties, such as heat capacity or viscosity, can be derived from properties obtained from the EOS models, such as fluid composition.

Further, the EOS models can be extended with other reservoir evaluation techniques for compositional simulation of flow and production behavior of the petroleum fluid of the reservoir, as is known in the art.

Further, an EOS that describes the distribution of a solid fraction of the reservoir fluid (e.g., asphaltenes, resins, and/or the like), may be used. In one implementation, such EOS may include the Flory-Huggins-Zuo EOS, which may be used with the Yen-Mullins model, which describes the physical nature of asphaltenes in crude. Such a combination may be used to provide a description of a baseline thermodynamic equilibrium state of a hydrocarbon column that includes gas, liquid, and solid petroleum components.

In one implementation, an EOS model may predict compositional gradients with depth that take into account the impacts of gravitational forces, chemical forces, temperature gradient, and/or the like. To calculate compositional gradients with depth in a hydrocarbon reservoir, it may be assumed that the reservoir fluids are connected (i.e., there is a lack of compartmentalization) and in thermodynamic equilibrium. In particular, it may be assumed that the reservoir fluids are in thermodynamic equilibrium with substantially little adsorption phenomena, addition of matter to the reservoir, pressure gradients other than gravity, heat fluxes across system boundaries, and/or chemical reactions in the reservoir.

Further, in order to identify variations in fluid properties of the reservoir via a downhole fluid analysis (DFA), one or more in situ reservoir fluid samples may be withdrawn using a downhole tool, or formation tester disposed within a wellbore. In particular, the reservoir fluid samples may be withdrawn from one or more reference points disposed in the wellbore. A reference point in the wellbore may be referred to as a measurement station.

As further discussed above, the DFA may then be performed at one or more measurement stations to determine one or more fluid properties of the reservoir fluid, including, but not limited to, gas-oil ratio (GOR), fluid composition (e.g., fractional amounts of C₁, C₂, C₃-C₅, C₆₊, CO₂, and the like), acidity of the fluids (e.g., pH), fluorescence, optical density, fluid resistivity, fluid density, and fluid viscosity. The downhole tool may also provide measurements of pressure, temperature, and mobility of the reservoir rock. As noted above, variations in such fluid properties may indicate the presence of heavy hydrocarbons, compartmentalization, and non-equilibrium hydrocarbon distribution in the reservoir.

The DFA may be performed on the reservoir fluid samples during drilling or thereafter. In one implementation, the reservoir fluid samples may be analyzed downhole during a pause in drilling operations, during which the downhole tool may acquire the fluid samples and transmit results of the DFA to an acquisition unit at the surface. In another implementation, the reservoir fluid samples may be analyzed on the surface after the drilling operations have finished, where the downhole tool may acquire the fluid samples and subsequently transmit the fluid samples to the surface for other fluid analysis to be performed. In yet another implementation, the DFA may be performed in real-time or substantially real-time.

Downhole Fluid Analysis Systems

FIGS. 4 and 5 illustrate various implementations of well site systems that may employ DFA systems and techniques. In one implementation, FIG. 4 illustrates a rig 400 with a downhole tool 402 in accordance with implementations of various technologies and techniques described herein. In particular, FIG. 4 depicts the downhole tool 402 as being suspended from the rig 400 and into a wellbore 404 via a drill string 406. The rig 400 may be similar to the rig 128 of FIGS. 1.2-1.3. The downhole tool 400 may have a drill bit 408 at its lower end that may be used to advance the downhole tool 400 into the formation, and may also be used to form the wellbore 404. The drill string 406 may be rotated by a rotary table 410 energized by a powering means (not shown), where the rotary table 410 may engage a Kelly joint 412 at the upper end of the drill string 406. The drill string 406 may be suspended from a hook 414 attached to a traveling block (not shown). In particular, the drill string 406 may be suspended through the Kelly joint 412 and a rotary swivel 416 that permits rotation of the drill string 406 relative to the hook 414. The rig 400 may be a land-based platform and derrick assembly used to form the wellbore 404 by rotary drilling. However, in other implementations, the rig 400 may be an offshore platform.

Drilling fluid or mud 418 may be stored in a pit 420 formed at the well site. A pump 422 may deliver the drilling fluid 418 to the interior of the drill string 406 via a port in the swivel 416, inducing the drilling fluid to flow downwardly through the drill string 406 as indicated by a directional arrow 424. The drilling fluid may exit the drill string 406 via ports in the drill bit 408, and then circulate upwardly through the region between the outside of the drill string and the wall of the wellbore, called the annulus, as indicated by directional arrows 426. The drilling fluid may lubricate the drill bit 408 and carry formation cuttings up to the surface as the fluid is returned to the pit 420 for recirculation.

The downhole tool 402 may sometimes be referred to as a bottom hole assembly (BHA), where the downhole tool 402 may be positioned near the drill bit 408. The BHA of FIG. 4 may be similar to the BHA of FIG. 1.2. The downhole tool 402 may include various components with capabilities, such as measuring, processing, and storing information, as well as communicating with the surface. A telemetry device (not shown) also may be provided for communicating with a surface unit (not shown).

The downhole tool 402 may also include a sampling system 428, where the sampling system 428 includes a fluid communication module 430 and a sampling module 432. The modules may be housed in a drill collar for performing various formation evaluation functions, such as pressure testing, sampling, and/or the like. As shown in FIG. 4, the fluid communication module 430 may be positioned adjacent to the sampling module 432. However, the position of the fluid communication module 430, as well as other modules, may vary in other implementations. Additional devices, such as pumps, gauges, sensor, monitors, and/or other devices usable in downhole sampling and/or testing may also be used. The additional devices may be incorporated into modules 430 and 432 or disposed within separate modules included within the sampling system 428.

The fluid communication module 430 may include a probe 434, where the probe 434 may be positioned in a stabilizer blade or rib 436. The probe 434 may include one or more inlets for receiving reservoir fluid and one or more flow lines (not shown) extending into the downhole tool for passing fluids through the tool. In another implementation, the probe 434 may include a single inlet designed to direct reservoir fluid into a flow line within the downhole tool. In yet another implementation, the probe may include multiple inlets that may be used for focused sampling. In such implementations, the probe may be connected to a sampling flow line, as well as to guard flow lines. The probe 434 may be movable between extended and retracted positions for selectively engaging a wall 403 of the wellbore 404 and acquiring fluid samples from a formation F. One or more setting pistons 438 may be provided to assist in positioning the fluid communication module 430 against the wellbore wall.

In another implementation, FIG. 5 illustrates a wireline downhole tool 500 in accordance with implementations of various technologies and techniques described herein. The downhole tool 500 may be suspended in a wellbore 502 from the lower end of a multi-conductor cable 504 that is spooled on a winch at the surface. The cable 504 may be communicatively coupled to an electronics and processing system 506. The downhole tool 500 may include an elongated body 508 that houses modules 510, 512, 514, 522, and 524. The modules 510, 512, 514, 522, and 524 may provide various functionalities, including, but not limited to, fluid sampling, pressure transient testing, fluid testing, operational control, communication, and/or the like. The modules 510 and 512 may provide additional functionality, for example resistivity measurements, operational control, communications, coring, imaging, fluid analysis, and/or the like.

As shown in FIG. 5, the module 514 may be a communication module and/or fluid analysis module 514 that has a selectively extendable probe 516 and backup pistons 518 that are arranged on opposite sides of the elongated body 508. The extendable probe 516 may be configured to selectively seal off or isolate selected portions of the wall 503 of the wellbore 502 to fluidly couple to the adjacent formation 520 and/or to draw fluid samples from the formation 520. The probe 516 may include a single inlet or multiple inlets designed for guarded or focused sampling. The reservoir fluid may be expelled to the wellbore through a port in the body 508, or the reservoir fluid may be sent to one or more fluid sampling modules 522 and 524. The fluid sampling modules 522 and 524 may include sample chambers that store the reservoir fluid. In addition, the electronics and processing system 506 and/or a downhole control system may be configured to control the extendable probe assembly 516 and/or the drawing of a fluid sample from the formation 520.

In yet another implementation, fluid from the reservoir of interest may be passed by means of a primary flow line (not shown) to the fluid analyzer module 514 for analysis. The fluid analyzer module 514 may be employed to provide DFA measurements. For example, the fluid analyzer module 514 may include an optical spectrometer and/or a gas analyzer designed to measure properties such as, optical density, fluid fluorescence, fluid composition, the GOR, and/or the like. In particular, the spectrometer may employ one or more optical filters to identify the color (i.e., the optical density) of the reservoir fluid. Such color measurements may be used for fluid identification, determination of asphaltene content, and/or pH measurement. The reservoir fluids may exhibit different colors because they have varying amounts of aromatics, resins, and asphaltenes, each of which absorb light in the visible and near-infrared (“NIR”) spectra. Heavy oils may have higher concentrations of aromatics, resins, and asphaltenes, which give them dark colors. Light oils and condensate, on the other hand, may have lighter, yellowish or bluish colors because they have lower concentrations of aromatics, resins, and asphaltenes.

One or more additional measurement devices, such as temperature sensors, pressure sensors, viscosity sensors, density sensors, resistivity sensors, chemical sensors (e.g., for measuring pH or H₂S levels), and gas chromatographs may also be included within the fluid analyzer module 514. In one implementation, the fluid analyzer module 514 may measure absorption spectra and translate such measurements into concentrations of several alkane components and groups in the fluid sample. For example, the fluid analyzer module 514 may determine the concentrations (e.g., weight percentages) of carbon dioxide (CO₂), methane (CH₄), ethane (C₂H₆), the C₃-C₅ alkane group, and the lump of hexane and heavier alkane components (C₆₊).

The fluid analysis module 514 may also include a controller (not shown), such as a microprocessor or control circuitry, designed to calculate certain fluid properties based on the sensor measurements. For example, the controller may calculate the GOR. Further, the controller may govern sampling operations based on the fluid measurements or properties. Moreover, the controller may be disposed within another module of the downhole tool 500.

The downhole tools described above with respect to FIGS. 4 and 5 may also be referred to as formation testers. Besides the implementations disclosed in FIGS. 4 and 5, other implementations of well site systems employing DFA systems and techniques known to those skilled in the art may be used. One example of a downhole tool which may be used to employ such systems and techniques may include the Modular Formation Dynamics Tester (MDT®), which is a registered trademark of Schlumberger Technology Corporation. Further, examples of a fluid communication module and/or fluid analysis module may include the Composition Fluid Analyzer (CFA®), Live Fluid Analyzer (LFA®), or the In Situ Fluid Analyzer (IFA®), which are registered trademarks of Schlumberger Technology Corporation.

In one implementation, a computing system associated with the fluid communication module and/or fluid analysis module as described above, such as the controller, may be used to determine the properties of the reservoir fluid (e.g., optical color and density and thereby asphaltene content, GOR, etc.) in substantially real time. In another implementation, the computing system associated with the fluid communication module and/or fluid analysis module may operate in conjunction with a surface computing system, such as the electronics and processing system 506 described above.

Further, other well logging instruments may be used in conjunction with the downhole tools described above, including those used to measure electrical resistivity, compressional and shear acoustic velocity, naturally occurring gamma radiation, gamma-gamma Compton scatter formation density, formation neutron hydrogen index (related to the fluid filled fractional volume of pore space of the rock formations), and/or nuclear magnetic resonance transverse and longitudinal relaxation time distribution and diffusion constant. In such an implementation, the well logging instruments, such as those that measure gamma radiation, may assist in identifying potential areas of interest in the subterranean formation. In particular, measurement stations may be assigned to these potential areas for the withdrawal of reservoir fluid samples.

As discussed above, a method for the integration of seismic data with downhole fluid analysis to predict the location of heavy hydrocarbon may be provided. The method may receive seismic data for a hydrocarbon reservoir of interest. The method may identify geological features associated with a secondary gas charge from the seismic data, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds. The method may determine the proximity of the geological features to the hydrocarbon reservoir of interest. The method may receive preliminary downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest. The method may analyze the preliminary DFA data to determine the equilibrium state of the hydrocarbon reservoir and to confirm the secondary gas charge in the hydrocarbon reservoir. The method may determine whether to perform one or more additional DFA's.

In some implementations, the method may make a determination of performing additional DFAs based on the proximity of the geological features and the analysis of the preliminary DFA data. The method may analyze the preliminary DFA data for fluid markers associated with the secondary gas charge in the hydrocarbon reservoir. The method may determine the proximity by determining whether the geological features are within a predetermined threshold spatial distance of the hydrocarbon reservoir. The method may further comprise determining whether the geological features are in fluid communication with the hydrocarbon reservoir. The method may analyze the preliminary DFA data to determine if the hydrocarbon reservoir is equilibrated using one or more equations of state models of thermodynamic behavior of reservoir fluid. The method may determine a geological age of the hydrocarbon reservoir based on the analysis of the equilibrium state of the hydrocarbon reservoir. The geological features may be gas chimneys and the method may further comprise a determination of the size of the gas chimneys. The method may perform one or more additional DFAs near the top of the hydrocarbon reservoir if the gas chimneys are classified as large. The method may perform one or more additional DFAs near the bottom of the hydrocarbon reservoir if the gas chimneys are classified as small. The method may determine the classification of a gas chimney as large if it is greater than one kilometer or comparable in size to the hydrocarbon reservoir, and as small if it is determined to be less than five hundred meters or less than one-third the size of the hydrocarbon reservoir. The method may further comprise predicting locations of one or more additional DFA stations based on the size of the gas chimneys. The method may use one or more additional DFAs to determine whether the hydrocarbon reservoir is in equilibrium or determine the presence of heavy hydrocarbon associated with the secondary gas charge. The method may use additional DFAs to determine the impact of heavy hydrocarbon for the purpose of flow assurance, defining a production strategy or field development planning. The method may further comprise identifying flow barriers caused by precipitation of solid particles or asphaltene from reservoir fluids. The method may comprise processing the seismic data to enhance the identification of one or more gas chimneys.

In some implementations, an information processing apparatus for use in a computing system is provided, and includes various means for receiving seismic data for a hydrocarbon reservoir of interest; identifying geological features associated with a secondary gas charge from the seismic data, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds; determining the proximity of the geological features to the hydrocarbon reservoir of interest; receiving preliminary downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest; analyzing the preliminary DFA data to determine the equilibrium state of the hydrocarbon reservoir and to confirm the secondary gas charge in the hydrocarbon reservoir; and determining whether to perform one or more additional DFA's.

In some implementations, a computing system is provided that includes at least one processor, at least one memory, and one or more programs stored in the at least one memory, wherein the programs may include instructions, which when executed by the at least one processor cause the computing system to receive seismic data for a hydrocarbon reservoir of interest; identify geological features associated with a secondary gas charge from the seismic data, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds; determine the proximity of the geological features to the hydrocarbon reservoir of interest; receive preliminary downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest; analyze the preliminary DFA data to determine the equilibrium state of the hydrocarbon reservoir and to confirm the secondary gas charge in the hydrocarbon reservoir; and determine whether to perform one or more additional DFA's.

In some implementations, a method may receive seismic data for a hydrocarbon reservoir of interest. The method may identify geological features associated with a secondary gas charge from the seismic data, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds. The method may receive preliminary downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest. The method may analyze the preliminary DFA data for fluid markers associated with the secondary gas charge in the hydrocarbon reservoir of interest. The method may further determine whether secondary gas charge has occurred from the analysis of the preliminary DFA data. The method may predict the presence of large disequilibrium gas-oil-ratio (GOR) gradients and saturation pressure gradients in the hydrocarbon reservoir based on the determination of the secondary gas charge.

In some implementations, a non-transitory computer readable medium having stored thereon a plurality of computer-executable instructions which, when executed by a computer, cause the computer to receive seismic data for a hydrocarbon reservoir of interest. The computer-executable instructions may also cause the computer to identify geological features in seismic data that are associated with a secondary gas charge, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds. The computer-executable instructions may further cause the computer to receive downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest. The computer-executable instructions may further cause the computer to analyze the DFA data to determine the equilibrium state of the hydrocarbon reservoir and to confirm the secondary gas charge in the hydrocarbon reservoir. The computer-executable instructions may further cause the computer to predict one or more locations of heavy hydrocarbon within the hydrocarbon reservoir of interest based on the identified geological features.

The computer-executable instructions may also cause the computer to analyze the DFA data for fluid markers associated with the secondary gas charge in the hydrocarbon reservoir. Wherein, the computer-executable instructions may also cause the computer to determine whether the hydrocarbon reservoir is equilibrated based on the DFA data. The computer-executable instructions may cause the computer to determine the presence of large disequilibrium gas-oil-ratio (GOR) gradients and saturation pressure gradients in the hydrocarbon reservoir of interest. The computer-executable instructions may also cause the computer to determine one or more locations of heavy hydrocarbon within the hydrocarbon reservoir of interest based on the size of the one or more gas chimneys.

Computing Systems

Implementations of various technologies described herein may be operational with numerous general purpose or special purpose computing system environments or configurations. Examples of well-known computing systems, environments, or configurations that may be suitable for use with the various technologies described herein include, but are not limited to, personal computers, server computers, hand-held or laptop devices, multiprocessor systems, microprocessor-based systems, set top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, smart phones, smart watches, personal wearable computing systems networked with other computing systems, tablet computers, and distributed computing environments that include any of the above systems or devices, and the like.

The various technologies described herein may be implemented in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that performs particular tasks or implement particular abstract data types. While program modules may execute on a single computing system, it should be appreciated that, in some implementations, program modules may be implemented on separate computing systems or devices adapted to communicate with one another. A program module may also be some combination of hardware and software where particular tasks performed by the program module may be done either through hardware, software, or both.

The various technologies described herein may also be implemented in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network, e.g., by hardwired links, wireless links, or combinations thereof. The distributed computing environments may span multiple continents and multiple vessels, ships or boats. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

FIG. 6 illustrates a schematic diagram of a computing system 600 in which the various technologies described herein may be incorporated and practiced. Although the computing system 600 may be a conventional desktop or a server computer, as described above, other computer system configurations may be used.

The computing system 600 may include a central processing unit (CPU) 630, a system memory 626, a graphics processing unit (GPU) 631 and a system bus 628 that couples various system components including the system memory 626 to the CPU 630. Although one CPU is illustrated in FIG. 6, it should be understood that in some implementations the computing system 600 may include more than one CPU. The GPU 631 may be a microprocessor specifically designed to manipulate and implement computer graphics. The CPU 630 may offload work to the GPU 631. The GPU 631 may have its own graphics memory, or may have access to a portion of the system memory 626. As with the CPU 630, the GPU 631 may include one or more processing units, and the processing units may include one or more cores. The system bus 628 may be any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus also known as Mezzanine bus. The system memory 626 may include a read-only memory (ROM) 612 and a random access memory (RAM) 646. A basic input/output system (BIOS) 614, containing the basic routines that help transfer information between elements within the computing system 1300, such as during start-up, may be stored in the ROM 612.

The computing system 600 may further include a hard disk drive 650 for reading from and writing to a hard disk, a magnetic disk drive 652 for reading from and writing to a removable magnetic disk 656, and an optical disk drive 654 for reading from and writing to a removable optical disk 658, such as a CD ROM or other optical media. The hard disk drive 650, the magnetic disk drive 652, and the optical disk drive 654 may be connected to the system bus 628 by a hard disk drive interface 656, a magnetic disk drive interface 658, and an optical drive interface 650, respectively. The drives and their associated computer-readable media may provide nonvolatile storage of computer-readable instructions, data structures, program modules and other data for the computing system 600.

Although the computing system 600 is described herein as having a hard disk, a removable magnetic disk 656 and a removable optical disk 658, it should be appreciated by those skilled in the art that the computing system 600 may also include other types of computer-readable media that may be accessed by a computer. For example, such computer-readable media may include computer storage media and communication media. Computer storage media may include volatile and non-volatile, and removable and non-removable media implemented in any method or technology for storage of information, such as computer-readable instructions, data structures, program modules or other data. Computer storage media may further include RAM, ROM, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other solid state memory technology, CD-ROM, digital versatile disks (DVD), or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by the computing system 600. Communication media may embody computer readable instructions, data structures, program modules or other data in a modulated data signal, such as a carrier wave or other transport mechanism and may include any information delivery media. The term “modulated data signal” may mean a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media may include wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. The computing system 600 may also include a host adapter 633 that connects to a storage device 635 via a small computer system interface (SCSI) bus, a Fiber Channel bus, an eSATA bus, or using any other applicable computer bus interface. Combinations of any of the above may also be included within the scope of computer readable media.

A number of program modules may be stored on the hard disk 650, magnetic disk 656, optical disk 658, ROM 612 or RAM 616, including an operating system 618, one or more application programs 620, program data 624, and a database system 648. The application programs 620 may include various mobile applications (“apps”) and other applications configured to perform various methods and techniques described herein. The operating system 618 may be any suitable operating system that may control the operation of a networked personal or server computer, such as Windows XP, Mac OS X, Unix-variants (e.g., Linux and BSD), and the like.

A user may enter commands and information into the computing system 600 through input devices such as a keyboard 662 and pointing device 660. Other input devices may include a microphone, joystick, game pad, satellite dish, scanner, or the like. These and other input devices may be connected to the CPU 630 through a serial port interface 642 coupled to system bus 628, but may be connected by other interfaces, such as a parallel port, game port or a universal serial bus (USB). A monitor 634 or other type of display device may also be connected to system bus 628 via an interface, such as a video adapter 632. In addition to the monitor 634, the computing system 600 may further include other peripheral output devices such as speakers and printers.

Further, the computing system 600 may operate in a networked environment using logical connections to one or more remote computers 674. The logical connections may be any connection that is commonplace in offices, enterprise-wide computer networks, intranets, and the Internet, such as local area network (LAN) 656 and a wide area network (WAN) 666. The remote computers 674 may be another a computer, a server computer, a router, a network PC, a peer device or other common network node, and may include many of the elements describes above relative to the computing system 600. The remote computers 674 may also each include application programs 670 similar to that of the computer action function.

When using a LAN networking environment, the computing system 600 may be connected to the local network 676 through a network interface or adapter 644. When used in a WAN networking environment, the computing system 600 may include a router 664, wireless router or other means for establishing communication over a wide area network 666, such as the Internet. The router 664, which may be internal or external, may be connected to the system bus 628 via the serial port interface 652. In a networked environment, program modules depicted relative to the computing system 600, or portions thereof, may be stored in a remote memory storage device 672. It will be appreciated that the network connections shown are merely examples and other means of establishing a communications link between the computers may be used.

The network interface 644 may also utilize remote access technologies (e.g., Remote Access Service (RAS), Virtual Private Networking (VPN), Secure Socket Layer (SSL), Layer 2 Tunneling (L2T), or any other suitable protocol). These remote access technologies may be implemented in connection with the remote computers 674.

It should be understood that the various technologies described herein may be implemented in connection with hardware, software or a combination of both. Thus, various technologies, or certain aspects or portions thereof, may take the form of program code (i.e., instructions) embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other machine-readable storage medium wherein, when the program code is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the various technologies. In the case of program code execution on programmable computers, the computing device may include a processor, a storage medium readable by the processor (including volatile and non-volatile memory and/or storage elements), at least one input device, and at least one output device. One or more programs that may implement or utilize the various technologies described herein may use an application programming interface (API), reusable controls, and the like. Such programs may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) may be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language, and combined with hardware implementations. Also, the program code may execute entirely on a user's computing device, on the user's computing device, as a stand-alone software package, on the user's computer and on a remote computer or entirely on the remote computer or a server computer.

The system computer 600 may be located at a data center remote from the survey region. The system computer 600 may be in communication with the receivers (either directly or via a recording unit, not shown), to receive signals indicative of the reflected seismic energy. These signals, after conventional formatting, and other initial processing, may be stored by the system computer 600 as digital data in the disk storage for subsequent retrieval and processing in the manner described above. In one implementation, these signals and data may be sent to the system computer 600 directly from sensors, such as geophones, hydrophones and the like. When receiving data directly from the sensors, the system computer 600 may be described as part of an in-field data processing system. In another implementation, the system computer 600 may process seismic data already stored in the disk storage. When processing data stored in the disk storage, the system computer 600 may be described as part of a remote data processing center, separate from data acquisition. The system computer 600 may be configured to process data as part of the in-field data processing system, the remote data processing system or a combination thereof.

Those with skill in the art will appreciate that any of the listed architectures, features or standards discussed above with respect to the example computing system 1300 may be omitted for use with a computing system used in accordance with the various embodiments disclosed herein because technology and standards continue to evolve over time.

Of course, many processing techniques for collected data, including one or more of the techniques and methods disclosed herein, may also be used successfully with collected data types other than seismic data. While certain implementations have been disclosed in the context of seismic data collection and processing, those with skill in the art will recognize that one or more of the methods, techniques, and computing systems disclosed herein can be applied in many fields and contexts where data involving structures arrayed in a three-dimensional space or subsurface region of interest may be collected and processed, e.g., medical imaging techniques such as tomography, ultrasound, MRI and the like for human tissue; radar, sonar, and LIDAR imaging techniques; and other appropriate three-dimensional imaging problems.

While the foregoing is directed to implementations of various technologies described herein, other and further implementations may be devised without departing from the basic scope thereof. Although the subject matter has been described in language specific to structural features or methodological acts, it is to be understood that the subject matter defined in the appended claims is not limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims. 

What is claimed is:
 1. A method, comprising: receiving seismic data for a hydrocarbon reservoir of interest; identifying geological features associated with a secondary gas charge from the seismic data, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds; determining the proximity of the geological features to the hydrocarbon reservoir of interest; receiving preliminary downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest; analyzing the preliminary DFA data to determine the equilibrium state of the hydrocarbon reservoir and to confirm the secondary gas charge in the hydrocarbon reservoir; and determining whether to perform one or more additional DFA's.
 2. The method of claim 1, wherein the determination of performing the additional DFAs are based on the proximity of the geological features and the analysis of the preliminary DFA data.
 3. The method of claim 1, wherein analyzing the preliminary DFA data comprises analyzing the preliminary DFA data for fluid markers associated with the secondary gas charge in the hydrocarbon reservoir.
 4. The method of claim 1, wherein determining the proximity comprises determining whether the geological features are within a predetermined threshold spatial distance of the hydrocarbon reservoir.
 5. The method of claim 1, further comprising determining whether the geological features are in fluid communication with the hydrocarbon reservoir.
 6. The method of claim 1, wherein analyzing the preliminary DFA data comprises determining if the hydrocarbon reservoir is equilibrated using one or more equations of state models of thermodynamic behavior of reservoir fluid.
 7. The method of claim 1 further comprising determining a geological age of the hydrocarbon reservoir based on the analysis of the equilibrium state of the hydrocarbon reservoir.
 8. The method of claim 1, wherein the geological features are gas chimneys and further comprising: determining the size of the gas chimneys; performing the one or more additional DFAs near the top of the hydrocarbon reservoir if the gas chimneys are classified as large; and performing the one or more additional DFAs near the bottom of the hydrocarbon reservoir if the gas chimneys are classified as small.
 9. The method of claim 8, wherein the gas chimneys are classified as large if it is determined to be greater than one kilometer or comparable in size to the hydrocarbon reservoir, and as small if it is determined to be less than five hundred meters or less than one-third the size of the hydrocarbon reservoir.
 10. The method of claim 1, further comprising predicting locations of one or more additional DFA stations based on the size of the gas chimneys.
 11. The method of claim 1, wherein the one or more additional DFAs determine whether the hydrocarbon reservoir is in equilibrium or determine the presence of heavy hydrocarbon associated with the secondary gas charge.
 12. The method of claim 1, wherein the additional DFAs are used to determine the impact of heavy hydrocarbon for the purpose of flow assurance, defining a production strategy or field development planning.
 13. The method of claim 1, further comprising identifying flow barriers caused by precipitation of solid particles or asphaltene from reservoir fluids.
 14. The method of claim 1, further comprising processing the seismic data to enhance the identification of one or more gas chimneys.
 15. A method, comprising: receiving seismic data for a hydrocarbon reservoir of interest; identifying geological features associated with a secondary gas charge from the seismic data, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds; receiving preliminary downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest; analyzing the preliminary DFA data for fluid markers associated with the secondary gas charge in the hydrocarbon reservoir of interest; determining whether secondary gas charge has occurred from the analysis of the preliminary DFA data; and predicting the presence of large disequilibrium gas-oil-ratio (GOR) gradients and saturation pressure gradients in the hydrocarbon reservoir based on the determination of the secondary gas charge.
 16. A non-transitory computer readable medium having stored thereon a plurality of computer-executable instructions which, when executed by a computer, cause the computer to: receive seismic data for a hydrocarbon reservoir of interest; identify geological features in seismic data that are associated with a secondary gas charge, wherein the geological features are selected from a group consisting of one or more gas chimneys, bright spots and salt welds; receive downhole fluid analysis (DFA) data from formations at or near the hydrocarbon reservoir of interest; analyze the DFA data to determine the equilibrium state of the hydrocarbon reservoir and to confirm the secondary gas charge in the hydrocarbon reservoir; and predict one or more locations of heavy hydrocarbon within the hydrocarbon reservoir of interest based on the identified geological features.
 17. The non-transitory computer readable medium of claim 16, wherein the program instructions which cause the computer to analyze the DFA data comprise program instructions which cause the computer to analyze the DFA data for fluid markers associated with the secondary gas charge in the hydrocarbon reservoir.
 18. The non-transitory computer readable medium of claim 16, wherein the program instructions which cause the computer to analyze the DFA data comprise program instructions which cause the computer to determine whether the hydrocarbon reservoir is equilibrated based on the DFA data.
 19. The non-transitory computer readable medium of claim 16, wherein the program instructions which, cause the computer to determine whether the reservoir is equilibrated based on the DFA data comprise program instructions which cause the processor to determine the presence of large disequilibrium gas-oil-ratio (GOR) gradients and saturation pressure gradients in the hydrocarbon reservoir of interest.
 20. The non-transitory computer readable medium of claim 16, wherein the one or more locations of heavy hydrocarbon within the hydrocarbon reservoir of interest are based on the size of the one or more gas chimneys. 